The proliferation of textual data in society currently is overwhelming, in particular, unstructured textual data is being constantly generated via call centre logs, emails, documents on the web, blogs, tweets, custome...The proliferation of textual data in society currently is overwhelming, in particular, unstructured textual data is being constantly generated via call centre logs, emails, documents on the web, blogs, tweets, customer comments, customer reviews, etc.While the amount of textual data is increasing rapidly, users ability to summarise, understand, and make sense of such data for making better business/living decisions remains challenging. This paper studies how to analyse textual data, based on layered software patterns, for extracting insightful user intelligence from a large collection of documents and for using such information to improve user operations and performance.展开更多
Big data analysis(BDA)can increase the capability of supply chain analysis of manufacturing companies.Therefore,many manufacturing companies want to use BDA,but it has been seen that BDA implementation is difficult,es...Big data analysis(BDA)can increase the capability of supply chain analysis of manufacturing companies.Therefore,many manufacturing companies want to use BDA,but it has been seen that BDA implementation is difficult,especially in developing countries due to the existence of various barriers related to finance,government regulations,etc.This paper aims to investigate the barriers to BDA implementation in Iranian companies.In literature,limited work has been done on identifying barriers to implementing BDA in developing countries.In this regard,34 barriers were identified to BDA adoption in Iran by employing a literature review and feedback received from experts.Then,the most important barriers(14)were analyzed using integrated Interpretive Structural Modeling and MICMAC approach.Results show that two barriers;namely,lack of sufficient knowledge of senior managers and weakness of governance policies,are the most significant.Finally,crucial policy measures and recommendations are proposed to assist managers and government bodies.展开更多
摘要The proliferation of textual data in society currently is overwhelming, in particular, unstructured textual data is being constantly generated via call centre logs, emails, documents on the web, blogs, tweets, customer comments, customer reviews, etc.While the amount of textual data is increasing rapidly, users ability to summarise, understand, and make sense of such data for making better business/living decisions remains challenging. This paper studies how to analyse textual data, based on layered software patterns, for extracting insightful user intelligence from a large collection of documents and for using such information to improve user operations and performance.
摘要Big data analysis(BDA)can increase the capability of supply chain analysis of manufacturing companies.Therefore,many manufacturing companies want to use BDA,but it has been seen that BDA implementation is difficult,especially in developing countries due to the existence of various barriers related to finance,government regulations,etc.This paper aims to investigate the barriers to BDA implementation in Iranian companies.In literature,limited work has been done on identifying barriers to implementing BDA in developing countries.In this regard,34 barriers were identified to BDA adoption in Iran by employing a literature review and feedback received from experts.Then,the most important barriers(14)were analyzed using integrated Interpretive Structural Modeling and MICMAC approach.Results show that two barriers;namely,lack of sufficient knowledge of senior managers and weakness of governance policies,are the most significant.Finally,crucial policy measures and recommendations are proposed to assist managers and government bodies.